code: def setUp(self):
      # Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
      vocab = ["l", "o", "w", "e", "r", "s", "t", "i", "d", "n", "\u0120", "\u0120l", "\u0120n", "\u0120lo", "\u0120low", "er", "\u0120lowest", "\u0120newer", "\u0120wider", "\u0120hello", "\u0120world", "<unk>",]  # fmt: skip
      self.tmpdirname = tempfile.mkdtemp()
      vocab_tokens = dict(zip(vocab, range(len(vocab))))
      merges = [
          "#version: 0.2",
          "\u0120 l",
          "\u0120l o",
          "\u0120lo w",
          "e r",
          "",
      ]
      self.tags_dict = {"a": 0, "abbr": 1, "acronym": 2, "address": 3}
      self.special_tokens_map = {"unk_token": "<unk>"}
  
      self.vocab_file = os.path.join(
          self.tmpdirname, VOCAB_FILES_NAMES["vocab_file"]
      )
      self.merges_file = os.path.join(
          self.tmpdirname, VOCAB_FILES_NAMES["merges_file"]
      )
      self.tokenizer_config_file = os.path.join(
          self.tmpdirname, "tokenizer_config.json"
      )
  
      with open(self.vocab_file, "w", encoding="utf-8") as fp:
          fp.write(json.dumps(vocab_tokens) + "\n")
      with open(self.merges_file, "w", encoding="utf-8") as fp:
          fp.write("\n".join(merges))
      with open(
          self.tokenizer_config_file, "w", encoding="utf-8"
      ) as fp:
          fp.write(json.dumps({"tags_dict": self.tags_dict}))
  
      feature_extractor_map = {
          "feature_extractor_type": "MarkupLMFeatureExtractor"
      }
      self.feature_extraction_file = os.path.join(
          self.tmpdirname, FEATURE_EXTRACTOR_NAME
      )
      with open(
          self.feature_extraction_file, "w", encoding="utf-8"
      ) as fp:
          fp.write(json.dumps(feature_extractor_map) + "\n")
  
imports: import json
  import os
  import shutil
  import tempfile
  import unittest
  from typing import List
  from transformers import MarkupLMProcessor, MarkupLMTokenizer, PreTrainedTokenizer, PreTrainedTokenizerBase, PreTrainedTokenizerFast
  from transformers.models.markuplm.tokenization_markuplm import VOCAB_FILES_NAMES
  from transformers.testing_utils import require_bs4, require_tokenizers, require_torch, slow
  from transformers.utils import FEATURE_EXTRACTOR_NAME, cached_property, is_bs4_available, is_tokenizers_available
label_desc: Use image node_id 1 for calling the MarkupLMProcessorTest obj's underlying member method code with example usage: obj.setUp() without return types